class_docstr: A stream that generates the entire history of a stream at each time step.
  
  Parameters
  ----------
  min_periods : int, default 1
      The number of periods to wait before producing values from the aggregation
      function.
code: def forward(self) -> "List[float]":
      v = self.inputs[0].value
      if not np.isnan(v):
          self.history += [v]
      return self.history
  
imports: from typing import Callable, List
  import numpy
  from tensortrade.feed.core.base import Stream
  from tensortrade.feed.api.float import Float
label_desc: Use image node_id 2 for calling the Expanding obj's underlying member method code with example usage: obj.forward() and returns: self